What are the responsibilities and job description for the Staff Analytics Engineer position at thrively?
About the Opportunity
Thrively has partnered with a fast-growing technology company to identify a Staff Analytics Engineer (will consider a Sr Engineer as well) who will play a foundational role in building and scaling the organization's modern analytics platform.
This is a highly visible individual contributor opportunity for someone who enjoys solving complex data challenges, building trusted data products, and partnering closely with engineering, product, and business teams to deliver high-quality analytics at scale.
We're looking for someone who thinks beyond writing SQL. This role is about designing reusable data models, establishing engineering best practices, and creating the trusted data foundation that powers decision making across the business.
What You'll Own
You'll help design, build, and evolve the company's modern analytics platform, including:
- Scalable dbt models and transformation layers
- Enterprise semantic models and source-of-truth datasets
- Business-critical metrics and KPI definitions
- Analytics engineering standards and best practices
- Data quality, testing, and observability
- Documentation and governance across the analytics ecosystem
- Performance optimization for analytics workloads
- Collaboration between Engineering, Product, GTM, Finance, and Leadership
This role sits at the intersection of software engineering and business analytics, helping transform raw data into reliable, trusted products that teams depend on every day.
What You'll Be Responsible For
You'll serve as a senior technical contributor within the Analytics Engineering organization, partnering across multiple business functions to solve complex analytical challenges.
Success in this role requires balancing strong technical execution with business understanding. You'll help establish data modeling standards, review technical designs, mentor teammates, and influence the long-term direction of the analytics platform. We're looking for someone who enjoys solving foundational problems that improve how an entire organization works with data.
What Makes Someone Successful Here
The ideal candidate has likely spent much of their career building modern analytics platforms rather than focusing exclusively on dashboards or reporting.
You'll likely bring experience with:
- Analytics Engineering
- dbt
- Snowflake
- Advanced SQL
- Data Modeling
- Dimensional Modeling
- Semantic Layer Design
- Data Testing and Quality
- Modern ELT Pipelines
- Analytics Governance
- Performance Optimization
You understand that trustworthy, well-documented data products create significantly more business value than simply delivering reports quickly.
Technical Environment
Current technologies include many of the following:
- Snowflake
- dbt
- SQL
- Python
- Git
- Airflow or similar orchestration platforms
- Looker, Tableau, or Power BI
- CI/CD workflows
- Modern cloud-based analytics architecture
What We're Looking For
We're interested in candidates who bring:
- 7 years of experience in Analytics Engineering, Data Engineering, or Business Intelligence
- Deep expertise with dbt, Snowflake, and advanced SQL
- Strong understanding of dimensional modeling and modern data architecture
- Experience designing scalable, reusable data models
- Experience building trusted metrics and semantic layers
- Strong communication and stakeholder management skills
- Passion for mentoring teammates and elevating engineering standards
Why This Opportunity?
This is an opportunity to help shape the future of analytics at an innovative technology company investing heavily in its modern data platform. You'll work alongside talented engineers, influence technical direction, establish best practices, and build the trusted data foundation that supports product, finance, GTM, and executive decision making across the business. If you're energized by building scalable analytics platforms and solving meaningful data challenges, we'd love to connect.
Salary : $170,000 - $210,000